Source code for jax._src.scipy.stats.laplace

# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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#     https://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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import scipy.stats as osp_stats

from jax import lax
from jax._src.numpy.util import _wraps
from jax._src.numpy.lax_numpy import _promote_args_inexact, _constant_like


[docs]@_wraps(osp_stats.laplace.logpdf, update_doc=False) def logpdf(x, loc=0, scale=1): x, loc, scale = _promote_args_inexact("laplace.logpdf", x, loc, scale) two = _constant_like(x, 2) linear_term = lax.div(lax.abs(lax.sub(x, loc)), scale) return lax.neg(lax.add(linear_term, lax.log(lax.mul(two, scale))))
[docs]@_wraps(osp_stats.laplace.pdf, update_doc=False) def pdf(x, loc=0, scale=1): return lax.exp(logpdf(x, loc, scale))
[docs]@_wraps(osp_stats.laplace.cdf, update_doc=False) def cdf(x, loc=0, scale=1): x, loc, scale = _promote_args_inexact("laplace.cdf", x, loc, scale) half = _constant_like(x, 0.5) one = _constant_like(x, 1) zero = _constant_like(x, 0) diff = lax.div(lax.sub(x, loc), scale) return lax.select(lax.le(diff, zero), lax.mul(half, lax.exp(diff)), lax.sub(one, lax.mul(half, lax.exp(lax.neg(diff)))))